Top Machine Learning Jobs in Sacramento, CA

You will lead technical strategy and engineering for ML-powered messaging features at Airbnb, integrating solutions and collaborating with teams to enhance user communication. Responsibilities include system design, mentoring, and establishing engineering standards.

The AI Forward Deployed Engineer designs and implements AI solutions, collaborating with stakeholders, enhancing reliability, and producing reusable resources. Responsibilities include diagnosing AI solution issues and engaging with finance and data teams.

The Staff Machine Learning Engineer will lead AI initiatives, architect LLM systems, design evaluation frameworks, and mentor engineers.

The Staff Advanced Analyst will drive data analytics to improve CS Safety experiences, influence product decisions, and build measurement tools using data-driven insights.

The Director of Data Sciences leads a team in strategic initiatives, drives machine learning and AI solutions, and manages resources to enhance data-driven decision making across the business unit.

Lead the Marketplace engineering team to enhance the renter experience by developing scalable systems, managing teams, and collaborating with cross-functional stakeholders to drive product strategy.

As Engineering Manager for the Marketplace team, lead full-stack engineers, drive strategic vision, manage team processes, and enhance user experience using AI and ML innovations.

The Lead Product Manager, AI will identify and build AI-powered products, drive growth and customer experience, and collaborate with cross-functional teams.

The Customer Success Manager will manage post-sales relationships, drive customer engagement and ROI, and advocate for client needs within the Buzz Solutions platform.

The role involves leading a team to manage data strategies and analytics for Netflix Games, requiring expertise in data science, business analytics, and team management.

As a Solutions Engineer, you will drive sales growth, support partnerships, and deliver AI-driven solutions while collaborating with various teams.

The Product Manager will lead the development of data-driven product capabilities at Axuall, ensuring features are delivered on time and meet customer needs through collaboration with various teams.

As a Machine Learning Senior/Staff Engineer, you'll lead architectural decisions, enhance algorithms, develop features, and deploy scalable analytics and machine learning solutions, also mentoring team members.

The Machine Learning Engineer will design and build systems that improve the AI shopping agent by using real user feedback, focusing on feedback loops and metrics to enhance user interactions and agent performance.

Build and maintain MLOps pipelines, deploy and monitor ML models as scalable services, transform and integrate healthcare data (FHIR/HL7), ensure reproducible feature management, and uphold HIPAA/HITRUST security for production ML in clinical systems.

Design, build, and deploy scalable ML and AI systems for Airbnb Customer Support. Lead LLM-based solutions (fine-tuning, RAG, evaluation), collaborate cross-functionally, and drive early-stage ML initiatives to production.

Lead design, development, and productionization of advanced ML models and data pipelines. Drive architecture, experimentation, validation, and best practices while mentoring ML engineers and delivering scalable, business-driving AI solutions.

The role involves building bioinformatics and ML pipelines, analyzing multi-omics data, mentoring, and collaborating across teams to develop actionable insights and scientific breakthroughs.

Design and deliver customer experience solutions using machine learning techniques, analyze customer data, implement ML algorithms, and automate processes.

Work with the product team on automating data ETL pipelines, deploying ML models, and connecting ML models to user interfaces. Collaborate with cross-functional teams on product development.

Lead and build the companys ML function: define strategy, design production ML systems and infrastructure, own data and evaluation practices, write production code, integrate ML into products, and recruit and mentor an expanding ML team.

Define ML strategy and build production ML systems end-to-end (data pipelines, training, evaluation, inference). Own data strategy, integrate ML with product/backend, write production-quality code, and recruit and mentor the ML team while setting technical direction.

Lead a team of data scientists developing ML-driven products, managing infrastructure, training models, and ensuring production quality while collaborating with senior leadership.

Design, develop, and deploy machine learning models; analyze large datasets; build scalable data pipelines and distributed computing environments; integrate ML solutions with cross-functional teams; optimize performance and support production ML infrastructure.

Lead and grow a global data engineering and ML organization, design cloud-native data platforms and pipelines, deliver ML-powered products, establish engineering and MLOps best practices, and support sales through solutioning and client-facing technical leadership.